The receive signal processing path for an ultrasound imaging system processes signal information received from the beamformer for each acquired ultrasound scan line, typically with log amplification, envelope detection, and low pass video filtering prior to scan conversion and display. While video filtering objectives may be many, the filtering is typically done with a linear-phase low pass filter in order to limit noise and to shape the frequency response of the signal for display without significant spatial distortion. Typical requirements are that the video filters do not contribute group delay distortion in the passband where there is significant signal energy and that the filter response and bandwidth are approximately matched to the spectral characteristics of the transducer and system in each particular imaging mode.
The video path response is often varied using selectable filters in order to provide either smoother or sharper (i.e. crisper) looking edge detail in the image. For example, the video path may use a linear-phase filter with Gaussian-like magnitude response together with a selectable FIR high pass filter to "whiten" or "sharpen" the imaging frequency response. These filters can be set to make the image look more focused on edges and with higher contrast edge detail. Such filters may be used in combination with other enhancement filters and with a nonlinear mapping of video intensities in order to suppress the low level noise, improve contrast, and improve the dynamic range presentation of ultrasound images on the display.
The use of two-dimensional linear FIR "enhancement" filters on the detected scan data has been mentioned in the prior art for ultrasound systems. Such filters would typically be implemented in the signal path following scan line data accumulation memories and prior to scan conversion. The objectives of the two-dimensional image filtering can be many, including provisions for either smoother or sharper (i.e. crisper) looking edge detail in the image or to suppress noise tendencies in the speckle-like tissue regions at lower grey levels. The two-dimensional FIR filter may be implemented as a cascade of independent azimuth and range filters (i.e. separable form) or as a nonseparable two dimensional FIR kernel. Typical objectives are that the two-dimensional filter frequency response characteristics be approximately matched to the spectral characteristics of the transducer and system in a particular imaging mode to provide a "whitened" composite imaging response.
For the range coordinate, the resulting filtered signal spectrum is determined by the receive detected signal spectral characteristics resulting from transducer and system response. The system response includes the fixed video filters in the path, and the contribution of the two-dimensional FIR filter response. For the azimuthal coordinate, the filtered signal spectrum is determined by the sampled azimuthal signal resulting from the scanning process, the scan line density and azimuthal beam profile, and the azimuthal component of the two-dimensional FIR filter response. If a nonseparable filter kernel is used, the resulting spatial spectrum along a given direction will depend on the full two-dimensional frequency response contributors of image, transducer, beam point spread function, and other system response parameters.
The two-dimensional response of the video path is often varied using selectable filter tap spacings, line spacings, and tap weightings to provide either smoother or sharper (i.e. crisper) looking edge detail in the image. Low pass smoothing FIR filter responses can be used to smooth out speckle and make tissues look more uniform in contrast.
Heretofore, ultrasound video range filtering implementations have been restricted to selectable linear filters which have pre-determined frequency responses with different bandwidths. The different filter responses are typically set by the system operator. Some systems may have filters with gradual low pass response rolloff for restricting bandwidth or smoothing the image characteristics. Due to these filter limitations conventional ultrasound systems do not have the flexibility to optimize response for a wide range of transducer and imaging conditions.
Accentuation of background noise and the degradation of contrast resolution of subtle tissue textures and tissue-structural interfaces is a limitation in any linear image filter implementation that attempts to increase local contrast and sharpen the appearance of an image because, with linear filters, background noise and tissue speckle is enhanced to the same degree as structural interfaces.
The use of smoothing filter responses reduces noise and improves subtle tissue contrast uniformity, but at the expense of loss of edge detail and a duller looking image. Again, with linear filters, smoothing is accomplished for all signals--low level noise as well as strong signals with structural details that do not benefit from smoothing. Noise can be reduced by other methods such as temporal filtering, but in that case, not without some degradation of the temporal signal response.
Similarly, two-dimensional filtering implementations are typically very simple and restricted to selectable linear filters, cascaded range and azimuth filters (i.e. separable implementations), which have pre-determined frequency responses with different bandwidths. The different filter responses are typically set by the system operator or by the system software in conjunction with the scanning and scan conversion mode. Azimuthal filter sample spacing is typically fixed.
The accentuation of background noise and the degradation of contrast resolution of subtle tissue textures and tissue-structural interfaces is a limitation of any two-dimensional linear filtering scheme, too, which attempts to increase local contrast in both dimensions and thereby sharpen the appearance of an image. The use of smoothing filter responses reduces noise and improves subtle tissue textures, but at the expense of loss of edge detail, and contrast, resulting in a duller looking image.
In separable two-dimensional filter implementations which use, strong high pass responses on both axes, the axial and azimuthal edge response will be enhanced while the diagonal edge frequency response will be smoothed making the total response behavior sensitive to the orientation of edge detail.